Data Scientist – Supply Chain Optimisation

🕒 il y a 4 mois

🇬🇧 Royaume-Uni – Télétravail

⏰ Temps Plein

🟡 Intermédiaire

🟠 Senior

📊 Data Scientist

🇬🇧 Parrain de Visa de Travailleur Qualifié UK

Cette entreprise a parrainé des visas de Travailleur Qualifié du Royaume-Uni par le passé.

👻 Score fantôme 65%

Ce que ça veut dire : la probabilité que cette offre reste ouverte sans recrutement actif.Comment le lire : 60 % ou plus, on pense que c'est une offre fantôme. Un score plus bas est moins inquiétant.Comment on la calcule : ancienneté, republications, postes ouverts vs taille de l'équipe, rapidité de clôture, et si le salaire est indiqué.À noter : une estimation à partir de données publiques, pas un jugement sur l'entreprise. De vraies offres peuvent avoir un score élevé, alors prenez-le comme un indice, pas comme un fait.

Postuler Maintenant

Trouver des Emplois à Distance Similaires

Configurer une alerte email pour les nouveaux emplois

📊 Vérifiez votre score de CV pour ce poste

Améliorez vos chances d'obtenir un entretien en vérifiant votre score de CV avant de postuler.

Télécharger le CV

Ciena

Site WebLinkedInTous les Emplois

5001 - 10000 employés

Fondée en 1985

📡 Télécommunications

🔧 Matériel

💰 Series C en 1995-12

Telecommunications • Hardware • Networking

Ciena est un leader mondial dans les systèmes optiques et de routage, les services et les logiciels d'automatisation. Nous construisons les réseaux les plus adaptatifs au monde pour répondre aux demandes numériques toujours croissantes et offrir des expériences plus riches et plus connectées à tous les utilisateurs. Depuis plus de trois décennies, nous apportons notre sens inné de l'humanité à notre quête incessante d'innovation.

Description

• Design and implement operations research and optimization models for network design, inventory positioning, production and capacity planning, sourcing, scheduling, and transportation • Develop and evaluate classical machine learning and statistical models to improve supply chain performance, cost efficiency, service levels, and sustainability outcomes • Analyze, cleanse, and transform large datasets to generate actionable insights • Select and apply optimization, machine learning, and statistical approaches to solve complex supply chain problems • Validate model performance and assumptions, quantify uncertainty, and communicate trade-offs and recommendations • Implement production-ready analytical solutions using Python or comparable programming languages • Apply MLOps practices across the model lifecycle, including data and feature pipelines, experiment tracking, versioning, testing, deployment, monitoring, retraining, documentation, and governance • Partner with data engineering, architecture, platform, and business teams to develop and maintain reliable, scalable, explainable, and maintainable solutions • Create dashboards, presentations, and decision-support outputs for technical and non-technical audiences, including senior leaders

🎯 Exigences

• Degree in Data Science, Statistics, Mathematics, Operations Research, Computer Science, Engineering, or related quantitative discipline • 5+ years of experience in data science, operations research, analytics, or optimization roles in supply chain or similarly complex operational problem domains • Python and SQL for data preparation, exploratory analysis, model development, validation, and production-ready analytical solutions • Experience developing, validating, and interpreting classical machine learning and statistical models, including regression, classification, clustering, time-series forecasting, probabilistic models, and tree-based or ensemble methods • Experience formulating and solving operations research problems using linear programming, mixed-integer programming, constraint programming, simulation, heuristics, or metaheuristics • Experience with tools such as OR-Tools, Pyomo, Gurobi, or comparable solvers • Ability to select appropriate optimization, machine learning, statistical modeling, or combined approaches and connect outputs to business decisions • Full and unrestricted right to work in the United Kingdom • Ciena is unable to provide employment visa sponsorship for this position now or in the future • Nice to have: modern data platforms such as Snowflake and transformation tools such as dbt • Nice to have: MLOps practices, including experiment tracking, version control, automated testing, deployment pipelines, model registries, production monitoring, drift detection, retraining, rollback, and lifecycle documentation • Nice to have: cloud or enterprise machine learning platforms and engineering practices, including Dataiku, Databricks, Azure Machine Learning/Azure AI, MLflow, containerization, APIs, CI/CD tooling, and production observability • Nice to have: deep learning methods and neural network architectures • Nice to have: geospatial analytics, graph analytics, or network visualization tools • Nice to have: experience supporting global supply chain environments or complex organizational structures

🏖️ Avantages

• Flexible work environment • Individual growth opportunities • Well-being support • Belonging-focused culture • Diversity and inclusion commitment • Equal opportunity employment • Workplace accommodation measures